Bot stamina: examining the influence and staying power of bots in online social networks

Abstract

This study presents a novel approach to expand the emergent area of social bot research. We employ a methodological framework that aggregates and fuses data from multiple global Twitter conversations with an available bot detection platform and ultimately classifies the relative importance and persistence of social bots in online social networks (OSNs). In testing this methodology across three major global event OSN conversations in 2016, we confirmed the hyper-social nature of bots: suspected social bot accounts make far more attempts on average than social media accounts attributed to human users to initiate contact with other accounts via retweets. Social network analysis centrality measurements discover that social bots, while comprising less than 0.3% of the total corpus user population, display a disproportionately high level of structural network influence by ranking particularly high among the top users across multiple centrality measures within the OSN conversations of interest. Further, we show that social bots exhibit temporal persistence in centrality ranking density when examining these same OSN conversations over time.

Hybrid Intelligence Strategies for Identifying, Classifying and Analyzing Political Bots

“…The frequency and intensity of the bots we detected resembled those of previous studies (Bessi and Ferrara 2016;Forelle et al 2015;Schuchard et al 2019). Nonetheless, we did not detect the intent to engage other users in conversation, as seen in the bots detected in previous studies.…”

“…Previous research focused on creating techniques to automatically identify bots by analyzing messaging behavior in the Twitter ecosystem (Schuchard et al 2019;Badawy et al 2019;Lai et al 2019;Wang et al 2020;Zheng et al 2019). Bots' movement throughout Twitter was primarily analyzed so as to improve automatic detection systems.…”

Politics and Politeness: Analysis of Incivility on Twitter During the 2020 Democratic Presidential Primary

“…Similarly, Broniatowski et al (2018) found that bots often are able to erode public consensus and promote harmful misinformation, such as anti-vaccination propaganda. The effects of bots pose serious implications, as work from Schuchard et al (2019) indicates that bots are hyper-social accounts that display a disproportionately high level of structural network influence online. Thus, this implies that the online reach of bots spans far beyond the reach of an average human user (Schuchard et al, 2019).…”

“…The effects of bots pose serious implications, as work from Schuchard et al (2019) indicates that bots are hyper-social accounts that display a disproportionately high level of structural network influence online. Thus, this implies that the online reach of bots spans far beyond the reach of an average human user (Schuchard et al, 2019).…”

Spotting Political Social Bots in Twitter: A Use Case of the 2019 Spanish General Election

“…Such a strategy is indeed used by the bots to remain unveiled and, thus, attract humans that are encouraged to interact with automatic-generated content. Similarly, in [15], the relative importance and persistence of social bots were analyzed during 3 crucial events, namely: 2016 US presidential elections, the ongoing Ukrainian-Russian conflict, and the Turkish censorship implemented by the government. More specifically, the primary outcomes of the study showed that bots attempted to initiate contact with users at an extremely higher rate than human users.…”